{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline --no-import-all"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%bash\n",
      "exotxt ViscoplasticNeedlemanFullyPrescribedTension_WithFlaw.h ViscoplasticNeedlemanFullyPrescribedTension_WithFlaw.txt\n",
      "sed 's/-308/E-308/g' ViscoplasticNeedlemanFullyPrescribedTension_WithFlaw.txt > temp;"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "                           *** exotxt Version 1.23 ***\n",
        "                               Revised 2013/08/07                      \n",
        "\n",
        "                    EXODUSII DATABASE TO TEXT FILE TRANSLATOR\n",
        "\n",
        "                          Run on 2014-01-03 at 15:30:03\n",
        "\n",
        "               ==== Email gdsjaar@sandia.gov for support ====\n",
        "\n",
        "\n",
        " DATABASE INITIAL VARIABLES\n",
        "\n",
        " Peridigm\n",
        "\n",
        " Number of coordinates per node         =         3\n",
        " Number of nodes                        =         1\n",
        " Number of elements                     =         1\n",
        " Number of element blocks               =         1\n",
        "\n",
        " Number of node sets                    =         0\n",
        " Number of side sets                    =         0\n",
        "\n",
        " Number of global variables             =         2\n",
        " Number of variables at each node       =         0\n",
        " Number of variables at each element    =         0\n",
        "\n",
        "\n",
        "      201 time steps on the input database\n",
        "       1 time steps processed\n",
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        "     201 time steps processed\n",
        "\n",
        "    201 time steps have been written to the text file\n",
        "\n",
        " exotxt used 0.01 seconds of CPU time\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "run exoplot.py temp"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "var_names"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "array(['MAX_VON_MISES_STRESS', 'MIN_VON_MISES_STRESS'], \n",
        "      dtype='|S20')"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "eng_strain_Y = time_steps*0.001/1.0e-8"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(eng_strain_Y,data_vars[-2],eng_strain_Y,data_vars[-1]);\n",
      "plt.ylabel(\"Max/Min von Mises Stress\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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qSzEV1QLcnfhETyIiuVkN/7fffhtff/01Dhw4AJVKhUceeQQzZ86UpZiKGgEe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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10e7e0110>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%bash\n",
      "rm ViscoPlasticNeedlemanFullyPrescribedTension_WithFlaw.txt temp"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    }
   ],
   "metadata": {}
  }
 ]
}